American Society of Naturalists

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“Assessing behavioral associations in a hybrid zone through social network analysis: Complex assortative behaviors structure associations in a hybrid quail population”

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David M. Zonana, Jennifer M. Gee, Eli S. Bridge, Michael D. Breed, and Daniel F. Doak (June 2019)

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RFID data and social network analyses link phenotype and fine-scale social structure in a hybrid quail population

‘Birds of a feather flock together’—but how does this assortative behavior (i.e. ‘like with like’) shape animal social networks within natural hybrid zones?

An adult female California quail showing partial male plumage at Royal Carrizo, a highly admixed population within the hybrid zone between California and Gambel’s quail in the San Jacinto and Santa Rosa Mountains of Southern California.<br />(Credit: Dr. Jennifer Gee)
An adult female California quail showing partial male plumage at Royal Carrizo, a highly admixed population within the hybrid zone between California and Gambel’s quail in the San Jacinto and Santa Rosa Mountains of Southern California.
(Credit: Dr. Jennifer Gee)

Animals must identify, attract, and compete for mates before reproducing. These mating behaviors strongly influence whether closely related species will hybridize in areas where they co-occur. Yet, our understanding of how behavior affects hybridization between species is hindered by the fact that mating occurs within a complex web of social interactions that are challenging to characterize. The social structure in which animals live determines who they will encounter as potential mates and competitors, and therefore shapes the opportunity for hybridization. In this study, Zonana et al. combine high-resolution behavioral data (captured with RFID tags) and network analyses to test how sex, mass, and plumage traits correlate with social structure across an entire breeding, hybrid population of quail. Their study takes place within the hybrid zone between the California and Gambel’s quail, where the species’ ranges overlap in the deserts and mountains of Southern California. The authors find that social associations between these gregarious birds are strongest and most prevalent between individuals of the opposite sex, and these male-female associations disproportionately occur between individuals with similar mass and plumage traits that are shared by both males and females. Yet, the quail's social networks are random with respect to plumage traits that differ between the two species. The authors discuss how these complex patterns of behavior may facilitate hybridization between these species. The study demonstrates how network analyses can be used to test the influence of multiple traits on social associations (within and between both sexes and species) in natural, breeding populations. The authors’ framework provides a promising approach towards better understanding how animal behavior drives genetic exchange between populations and species.


Behavior can strongly influence rates and patterns of hybridization between animal populations and species. Yet few studies have examined reproductive behaviors in natural hybrid zones within the fine-scale social structure in which they take place. We use radio-frequency identification (RFID) tags with social network analyses to test whether phenotypic similarity in plumage and mass correlate with social behavior throughout a breeding season in a California and Gambel’s quail hybrid zone. We use a novel approach to partition phenotypic variation in a way that does not confound differences between sexes and species, and illustrate the complex ways that phenotype and behavior structure the social environment, mating opportunities, and male-male associations. Associations within the admixed population were random with respect to species-specific plumage, but showed strong patterns of assortment based upon sexually dimorphic plumage, monomorphic plumage, and mass. Weak behavioral reproductive isolation in this admixed population may be the result of complex patterns of phenotypic assortment based upon multiple traits, rather than a lack of phenotypic discrimination. More generally, our results inform the utility of social network analyses for analyzing behavioral factors affecting genetic exchange between populations and species.